On the use of fuzzy partitions to protect data

Article type: Research Article

Authors: Quirós, Pelayo^a | Alonso, Pedro^{a; *} | Díaz, Irene^b | Montes, Susana^c

Affiliations: [a] Department of Mathematics, University of Oviedo, Oviedo, Spain | [b] Department of Computer Science, University of Oviedo, Oviedo, Spain | [c] Department of Statistics and O.R., University of Oviedo, Oviedo, Spain

Correspondence: [*] Corresponding author: Pedro Alonso, Department of Mathematics, University of Oviedo, Avda. Calvo Sotelo s/n, Oviedo 33007, Spain. Tel.: +34 985 182 128; Fax: +34 985 103 354; E-mail: [email protected].

Abstract: Data protection is one of the most challenging tasks nowadays due to the huge amount of information that can be shared and crossed from different sources. Releasing microdata is a way to protect data, mainly in the economic and medical field. However, this kind of data can experience privacy attacks. This paper proposes the use of fuzzy sets as a way to improve the protection of privacy in microdata. Then, traditional definitions of k-anonymity, l-diversity and t-closeness are extended. The performance of these new approaches is checked in terms of the risk index.

Keywords: k-anonymity, l-diversity, t-closeness, fuzzy partition, data privacy

DOI: 10.3233/ICA-140473

Journal: Integrated Computer-Aided Engineering, vol. 21, no. 4, pp. 355-366, 2014